Plant roots determine carbon uptake, survivorship, and agricultural yield and represent a large proportion of the world’s vegetation carbon pool. Study of belowground competition, unlike aboveground shoot competition, is hampered by our inability to observe roots. We developed a consumer-resource model based in game theory that predicts the root density spatial distribution of individual plants and tested the model predictions in a greenhouse experiment. Plants in the experiment reacted to neighbors as predicted by the model’s evolutionary stable equilibrium, by both overinvesting in nearby roots and reducing their root foraging range. We thereby provide a theoretical foundation for belowground allocation of carbon by vegetation that reconciles seemingly contradictory experimental results such as root segregation and the tragedy of the commons in plant roots.
Community ecologists value the phenomenological observation of plant biotic interactions because they provide assumptions to make predictions of other ecosystem features, such as species diversity, community structure, or plant atmospheric carbon uptake. However, a rising number of scientists claim for the need of a mechanistic understanding of plant interactions, due to the limitations that a phenomenological approach raises both in empirical and modeling studies. Scattered studies take a mechanistic approach to plant interactions, but we still lack an integrated theoretical framework to start approaching holistically. In this Review and Synthesis, we present a comprehensive foundation for the study of the mechanisms underpinning the net interaction between two plants. First, we recapitulate the elementary units of plant interactions, i.e. all the known biophysical processes affected by the presence of an influencing plant and the possible phenotypic responses of influenced plants to these processes. Following, we discuss how a net interaction between two plants may emerge from the simultaneous effect of these elementary units. We then touch upon the spatial and temporal variability of this net interaction, and scrutinize how that variability may be linked to the underlying biophysical processes. We conclude by arguing how these processes can be integrated in a mechanistic framework for plant interactions, and why it must necessarily focus on the individual scale, incorporate the spatial structure of the community, and explicitly account for environmental factors.
The study of functional trait plasticity and optimal allocation strategies in a water competition context may help to explain the mechanisms relating plant competition to ecological semi-arid patterns. We measured four functional plant traits –root to shoot ratio, superficial to deep roots ratio, root diameter, and root estimated surface area to shoot ratio– in wild populations of two C4 grasses in a Kenyan savanna to assess their responses to different water inputs (changing with latitude) and soil drying rates (driven by canopy cover). Root:shoot allocation was different between the two species. We show that to account for root architecture helps understanding root allocation strategies, especially in species with high plasticity in root geometry. Concretely, in our case, a higher root allocation in wetter conditions was driven by water storage and not water foraging in the species with high root diameter variability. Superficial root allocation responded to changes associated with drying rates but not to water input, and shallower root systems developed under higher water stressconditions, supporting rainfall intermittency models of savanna tree-grass competition. We also suggest self-shading as a facilitation mechanism that may affect spatial patterns according to the scale-dependent feedback hypothesis.
AIM: To improve our knowledge of the process of selection of important plantareas (IPAs), a recent requirement of the Global Strategy for Plant Conserva-tion. The study was conducted at a hotspot of plant conservation in the Euro-pean continent, using a comprehensive database of plant species distribution inthe area.
METHODS: We used range distribution data for 3218 vascular plants found inSpain, in the form of 10 km UTM squares, totalling 169,124 species occur-rences across 5508 UTM cells. We identiﬁed IPAs by scoring threat status,endemism, rarity, phylogeny and species richness. We then performed two dif-ferent analyses, with and without incorporating the species richness score ofevery square. Finally, a null model was used to obtain a general pattern of spe-cies occurrences, we computed an index of occurrence richness (SI), and thenwe selected a number of speciﬁc territories of different sizes to reveal differ-ences in sampling effort within the study area.
RESULTS: We identiﬁed IPAs in Spain according to the proposed scoringmethod. We detected a positive relationship among richness and total scorecalculated with the rest of the criteria. However, endemism and threat statusproduced certain speciﬁc effects for species-poor squares. Regarding samplebias, we detected over- and under-recorded areas. This bias seems to be due tothe accumulation of ﬁeld prospecting in species-rich areas in detriment to poorareas.
MAIN CONCLUSIONS: We envisage two different approaches to address IPA selec-tion in hotspots. First, we advocate a complementary scoring-mapping methodfor areas where a relatively large amount of range distribution data and plantknowledge is available. Secondly, as richness per se encompasses a great amountof biogeographical information, we suggest using species richness or any otherenvironmental surrogate to delineate preliminary IPAs in poorly known butspecies-rich territories